Prospects for Working from Home: Assessing the evidence
This new iMOVE report distils all the work we’re doing in the area of Working from Home, along with our policy considerations and recommendations.
This new iMOVE report distils all the work we’re doing in the area of Working from Home, along with our policy considerations and recommendations.
Watch the recording of our ‘Digitisation of transport and freight: How are we tracking in Australia, and where are the opportunities?’ webinar.
A study of the attraction/retention of businesses/households to regional cities, & the long-term impacts of COVID on spatial patterns of employment/settlement.
The goal of this project is to recommend interventions and projects to turn streets into better public spaces by building on aspirations of the local community.
The objective of this PhD project is to analyse the relationship between telemetry and its impact on commercially sustainable transportation solutions/networks.
Watch the video recording of our webinar discussing the final report of our ‘Innovative local transport: Community transport of the future’ project.
Download the final report from iMOVE’s ‘Innovative local transport: Community transport of the future’ project.
Literature review/stakeholder interviews to guide the estimation of the extent, spatial distribution, & nature of transport disadvantage in the Greater Perth region.
Register for our webinar ‘Delivering community transport that meets the diverse needs of our growing population’, and improve its service and accessibility.
A scoping study to identify opportunities to improve urban freight planning tertiary education in Australia, improving education outcomes for freight logistics.
Our ‘Encouraging continuation of work from home post-pandemic’ project has been completed, and the final report is available here.
This PhD project will develop traffic management strategies and infrastructure allocation algorithms needed to improve emergency vehicle logistics.
This project will create a model for estimating delays at Perth’s traffic signals, which would inform project decisions and operational strategies.
Using state-of-the-art machine learning algorithms, this study will use a novel modelling approach to accurately predict traffic crashes in real-time.
This PhD project will, at its conclusion, demonstrate how the roles and responsibilities of different stakeholders impact building a collaborative MaaS environment.
This PhD project explores cycle lane implementation from both a policymaker’s and user’s perspective, and flexible transport solutions for rural users.